SOLID principles are quite well known nowadays, but do you know their cousin, the Principles for Package and Component Design? Okay, maybe it's not the catchiest name, but that's what Robert C. Martin named them in his book entitled Agile Software Development, Principles, Patterns, and Practices. 

(The following article is property of Avenue Code, LLC, and was originally published with permission at TotalRetail on August 9, 2019.) 

Retail strategist Carl Boutet discusses the cultural and technological transformations retailers must make to create personalization and consistency across physical and digital platforms.

What is Elasticsearch, how does it work, and why is it so effective? Elasticsearch is simple to configure, has incredible flexibility, and is an excellent tool for complex searches. Let's take a closer look.

Over the years, Swift has become a very powerful language with many features, and one of the greatest of Swift's powers is generics.

Welcome to the second part of our Snippets series on real-time stream processing using Apache Kafka! To recap, in part one we introduced stream processing and discussed some of the challenges involved, like the stateful nature of aggregations and joins. We’ll discuss the impact of such stateful operations in a while, but first, let’s delve deeper into one key aspect of real-time stream processing: performance.

Apache Kafka is probably primarily known as a messaging middleware with a more flexible structure than queues, but it also empowers teams with its lower entry barrier for real-time data pipelines.

For many years, I was a big fan of beautiful code. With Ruby, I was amazed by what I was able to do in one line of code. With Java, I loved that I could stream, map, and then collect! But as time passed, I read about many impressive optimizations, small tricks, and clever algorithms, and I got less and less excited about these discoveries.